University Teachers’ Digital Competence and AI Literacy: Moderating Role of Gender, Age, Experience, and Discipline

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Dear Authors,

Congratulations on your work! The article meets the requirements of a research work. The descriptive statistics from the research data are clearly reported and presented in some tables and figures. I missed the conceptualisation of your research method. In the text p.5-223, they say, ‘The data collection was conducted using a questionnaire (MS Forms)’ and then describe the research period, subjects etc. What was the scientific-methodological approach used?

Another point to review is that they mention that the higher education institutions were selected based on ‘expert selection’. How did this happen? The selection of experts is a methodological approach not specified in this study.

Keep in mind that the discussion of the results is extensive and dense, which can make it difficult to read, but it is pertinent for an in-depth understanding of the analysis of the data and its articulation with the objectives of the study.

In the sample, p. 5 - 235, they write 48,878 years (SD = 10,878). Suggestion: for the reader's better understanding, use only 1 decimal place - 48.8 / 10.8 - is this possible?

Figures 1 and 2 are not properly cited in the body of the text, which affects the fluidity and comprehension of the reading. In addition, both have poor image quality. Figure 2 is practically illegible. We need to improve the resolution of images 1 and 2 and ensure that they are correctly inserted and referenced in the body of the text.

Author Response

Thank you very much for taking the time to review our manuscript. Thank you for your kind and constructive suggestions, which have helped us to improve our article. Please find the detailed responses below and the corresponding corrections highlighted in the re-submitted files.

Comments 1:

I missed the conceptualisation of your research method. In the text p.5-223, they say, ‘The data collection was conducted using a questionnaire (MS Forms)’ and then describe the research period, subjects etc. What was the scientific-methodological approach used?

Response 1:

Thank you for pointing this out. We agree with this comment. Therefore, we described the scientific-methodological approach (p. 5-237).

Comments 2:

Another point to review is that they mention that the higher education institutions were selected based on ‘expert selection’. How did this happen? The selection of experts is a methodological approach not specified in this study.

Response 2:

Agree. We have, accordingly, detailed the selection of experts (p. 5-241).

Comments 3:

Keep in mind that the discussion of the results is extensive and dense, which can make it difficult to read, but it is pertinent for an in-depth understanding of the analysis of the data and its articulation with the objectives of the study.

Response 3:

Thank you for pointing this out. We agree with this comment. Therefore, chapter 4 has been divided into subsections, and chapter 5 has been supplemented in order to make it easier to read.

Comments 4:

In the sample, p. 5 - 235, they write 48,878 years (SD = 10,878). Suggestion: for the reader's better understanding, use only 1 decimal place - 48.8 / 10.8 - is this possible?

Response 4:

Thank you for the suggestion, we have corrected the numbers based on this (p. 6-254 and p. 6-255).

Comments 5:

Figures 1 and 2 are not properly cited in the body of the text, which affects the fluidity and comprehension of the reading. In addition, both have poor image quality. Figure 2 is practically illegible. We need to improve the resolution of images 1 and 2 and ensure that they are correctly inserted and referenced in the body of the text.

Response 5:

Thank you for pointing this out, we have improved the image quality, increased the font size of the figure captions and cited the figures in the body of the text (p. 8-349, p. 10-395).

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for this opportunity to read your paper. This study makes a valuable empirical contribution to AI literacy research, particularly in a Hungarian context. 

Strengths of the Study

   - The paper draws on recent, high-impact studies to frame its discussion, ensuring alignment with contemporary debates on AI in education. 

   - The research gap is well-articulated, particularly the need for empirical evidence on how digital literacy relates to AI literacy among university teachers—a previously understudied population in Hungary. 

   - The findings support tailored AI training programs (e.g., gender- and experience-specific approaches), echoing UNESCO’s competency framework. 

   - The flow from introduction to conclusion is coherent, with results directly addressing the implied research goals. 

Areas for Improvement

   - The current title of the paper is overly broad. Refocus to highlight the study’s unique contribution. Reframe the title to accurately reflect the study’s focus on digital literacy’s role and moderation effects.

   - The paper tests relationships (e.g., digital literacy and AI literacy + moderation by gender/experience) without stating formal research questions or hypotheses, which risks appearing exploratory. Introduce explicit guiding research questions/hypotheses to strengthen theoretical grounding.

   - Some citations (e.g., Al-Riyami et al., 2023) are repetitively used for minor claims. Prune redundant citations and diversify evidence, especially for contested findings.

   - The Data Analysis and Results sections are dense and would benefit from subsections to improve navigation. 

Comments on the Quality of English Language

The manuscript would benefit from thorough English language editing to improve fluency and precision. Professional proofreading would enhance readability for an international audience.

Author Response

Thank you very much for taking the time to review our manuscript. Thank you for your kind and constructive suggestions, which have helped us to improve our article. Please find the detailed responses below and the corresponding corrections highlighted in the re-submitted files.

Comments 1:

The current title of the paper is overly broad. Refocus to highlight the study’s unique contribution. Reframe the title to accurately reflect the study’s focus on digital literacy’s role and moderation effects.

Response 1:

Thanks for pointing this out, we've changed the title.

Comments 2:

The paper tests relationships (e.g., digital literacy and AI literacy + moderation by gender/experience) without stating formal research questions or hypotheses, which risks appearing exploratory. Introduce explicit guiding research questions/hypotheses to strengthen theoretical grounding.

Response 2:

Thank you for the development suggestion, based on this we have introduced research questions (p. 5-227).

Comments 3:

Some citations (e.g., Al-Riyami et al., 2023) are repetitively used for minor claims. Prune redundant citations and diversify evidence, especially for contested findings.

Response 3:

Thanks for pointing this out, based on this, we reorganized the references and diversified the evidence.

Comments 4:

The Data Analysis and Results sections are dense and would benefit from subsections to improve navigation.

Response 4:

Agree. Chapter 4 has been divided into subsections.

Comments 5:

The manuscript would benefit from thorough English language editing to improve fluency and precision. Professional proofreading would enhance readability for an international audience.

Response 5:

Thank you for the development suggestion, based on this we have asked an English language reviewer to proofread our manuscript. Please see the attachment for his opinion.

Reviewer 3 Report

Comments and Suggestions for Authors

• The study examines the relationship between digital literacy and AI literacy among university teachers. It examines whether this relationship is affected by gender, age, discipline, and teaching experience among Hungarian university teachers.
• The topic is original because it covers 1103 university teachers from various disciplines in Hungary, which allows for a systematic study and can serve as an example for research in other countries, taking into account the specificities of education systems, and allows filling a significant gap in existing scientific research, which previously rarely covered the combination of gender, age, discipline, and teaching experience.
• The study adds substantial empirical evidence to the relationship between digital and AI literacy, focusing on demographic characteristics. Unlike other studies that have considered these factors separately, this one takes into account the complex interaction, which allows for a more precise understanding of the specifics of different groups (e.g., by gender or work experience). Although it is necessary to clarify the concepts that authors use regarding AI literacy and competence, and digital literacy and competence.
• It is worth considering the possibility of using additional qualitative methods (e.g., in-depth interviews or case studies) to deepen the understanding of individual motivations and contextual factors, to note what other factors influence teachers' AI competence. It is possible to more clearly define why selected demographic factors (gender, age, experience) are important in the context of AI competency development by referring to existing theoretical models or frameworks (e.g., UNESCO AI Competency Framework).
• It would be useful to note the effectiveness of different educational strategies based on the evidence obtained by the authors to support the formation of teachers' AI competence and how to assess the development of AI competence.
• The conclusions are consistent with the evidence presented in the study and answer the main question. The study confirms that digital competence is related to AI competence. Also, it shows the importance of considering gender and teaching experience as moderators, which is in line with the research objectives.
• The references are relevant, the authors refer to modern sources (e.g. UNESCO AI Competency Framework, DigCompEdu, etc.), emphasising the results' validity and relevance. It is also worth adhering to the conceptual apparatus under these sources.
• The tables presented are informative and clearly illustrate the main conclusions.

Author Response

Thank you very much for taking the time to review this manuscript. Please find the detailed responses below and the corresponding corrections highlighted in the re-submitted files.

Comments 1:

Although it is necessary to clarify the concepts that authors use regarding AI literacy and competence, and digital literacy and competence.

Response 1:

Thank you for bringing this to our attention. In the manuscript, we used the terms 'digital literacy' and 'digital competence' as synonyms. We have now removed the term 'digital literacy' from the text to avoid misunderstandings and defined the term digital competence (just like the term AI literacy) (7-276 and 7-286).

Comments 2:

It is worth considering the possibility of using additional qualitative methods (e.g., in-depth interviews or case studies) to deepen the understanding of individual motivations and contextual factors, to note what other factors influence teachers' AI competence.

Response 2:

Thank you for your suggestion, our qualitative study is underway to gain a deeper understanding of the connections.

Comments 3:

It would be useful to note the effectiveness of different educational strategies based on the evidence obtained by the authors to support the formation of teachers' AI competence and how to assess the development of AI competence.

Response 3:

Thank you for your suggestion, the study was supplemented (15-529).

Comments 4:

It is possible to more clearly define why selected demographic factors (gender, age, experience) are important in the context of AI competence development by referring to existing theoretical models or frameworks (e.g., UNESCO AI Competency Framework).

Response 4:

Thanks for pointing this out, references have been incorporated into the study.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for your thoughtful responses to my feedback. Regarding the title, I would still recommend refining it for conciseness - at 22 words, it currently exceeds the ideal length for maximum impact and readability.

Good luck

Author Response

Comment:

Regarding the title, I would still recommend refining it for conciseness - at 22 words, it currently exceeds the ideal length for maximum impact and readability.

Response:

Thanks for pointing it out. You're absolutely right, so we've shortened the title to 15 words, with the content unchanged.